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Enregistrement W1040989942 · doi:10.1182/blood.v124.21.621.621

Overall Survival in Older Patients with Newly Diagnosed Acute Myeloid Leukemia (AML) with >30% Bone Marrow Blasts Treated with Azacitidine By Cytogenetic Risk Status: Results of the AZA-AML-001 Study

2014· article· en· W1040989942 sur OpenAlexaff
Hartmut Döhner, John F. Seymour, Aleksandra Butrym, Agnieszka Wierzbowska, Dominik Selleslag, Jun Ho Jang, James D. Cavenagh, Rajat Kumar, Andre C. Schuh, Anna Candoni, Christian Récher, Irwindeep Sandhu, Haifa Kathrin Al‐Ali, Giovanni Martinelli, José Falantes, Richard M. Stone, Mark D. Minden, Heidi McIntyre, Stephen Songer, Lela M. Lucy, C.L. Beach, Hervé Dombret

Notice bibliographique

RevueBlood · 2014
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensUniversity of AlbertaPrincess Margaret Cancer CentreCancerCare Manitoba
Organismes subventionnairesnon disponible
Mots-clésMedicineAzacitidineInternal medicineMyeloid leukemiaOncologyBone marrowCytogeneticsDecitabineLeukemiaSurgery

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Overall survival (OS) in older patients (pts) with AML and poor-risk cytogenetics is only ~2-3 months (mos) (Burnett, Cancer, 2007). Often these pts receive only palliative treatment (Tx) with best supportive care (BSC). Low-dose Ara-C (LDAC) provides no OS benefit in pts with poor cytogenetics (Döhner, Blood, 2010). Typically, intensive chemotherapy (IC) is either not suitable for older AML pts with poor cytogenetics or, when it is used, provides no OS benefit (Kantarjian, Blood, 2010). The phase 3, multicenter, randomized, open-label AZA-AML-001 trial showed azacitidine (AZA) Tx in older pts with newly diagnosed AML (>30% bone marrow [BM] blasts) prolonged median OS by ~4 mos vs conventional care regimens (CCR) (10.4 vs 6.5 mos; p=0.1009) and improved 1-year survival (46.5% vs 34.2%) (Dombret, EHA, 2014). Cytogenetic risk is a prognostic indicator in elderly AML and a frequent determinant of Tx approach and outcomes. Objective: To determine the effect of Tx with AZA vs CCR on OS and 1-year survival in AZA-AML-001 pt subgroups based on cytogenetic risk classification. Methods: Pts aged ≥65 years with newly diagnosed de novo or secondary AML who were ineligible for transplant, with intermediate- or poor-risk cytogenetics (pts with favorable cytogenetics were excluded from study), ECOG performance status 0-2, and WBC count ≤15x109/L, were eligible. Before randomization, each pt was preselected to receive 1 of 3 commonly used CCR for older pts with AML, per investigator choice: IC (standard 7+3 regimen), LDAC (20 mg SC BID x 10 days/28-day cycle), or BSC only. Pts were then randomized to AZA (75 mg/m2/day SC x 7 days/28-day cycle) or to CCR, in which case they received their preselected Tx. The primary endpoint was OS. Cytogenetic risk groups were assessed per NCCN criteria by central review: intermediate (INT; all cases), intermediate with normal karyotype (cytogenetic normal [CN]), and poor. Survival at 1 year was compared between Tx. Median OS for AZA vs CCR was calculated using Kaplan-Meier methods, hazard ratios (HR) and 95% confidence intervals (CI) were determined by unstratified Cox proportional hazards model, and p values by log-rank test. Results: In all, 488 pts were randomized, 241 to AZA and 247 to CCR. Cytogenetic risk was balanced between Tx groups: 315 pts had INT-risk cytogenetics (AZA n=155 [64%], CCR n=160 [65%]), including 218 who were CN (AZA n=113 [73%], CCR n=105 [66%]), and 170 pts had poor-risk cytogenetics (AZA n=85 [35%], CCR n=85 [34%]). Within each of the 3 cytogenetic risk subgroups, the distribution of pts receiving individual CCR was very consistent: ~18% of each cytogenetic risk subgroup received BSC, ~64% received LDAC, and ~18% received IC. Baseline characteristics were generally balanced among the AZA and CCR Tx arms and the 3 cytogenetic risk groups (Table). At baseline, proportionately more pts with poor-risk cytogenetics in the AZA group were aged ≥75 years (57.6% vs 47.1% with CCR) and more pts in the CCR group had AML with myelodysplastic changes (45.9% vs 37.6% with AZA). Median OS (95%CI) in poor-risk pts was significantly prolonged with AZA vs CCR: 6.4 mos (4.2, 8.1) vs 3.2 mos (2.2, 4.7), respectively; HR=0.68 (0.50, 0.94), p=0.019 (Figure). Median OS in INT-risk pts was 13.0 mos (11.2, 16.3) vs 10.1 mos (7.1, 13.3) with AZA vs CCR; HR=0.90 (0.70, 1.16), p=0.41. Median OS in the CN subgroup was 14.1 mos (12.6, 19.5) vs 10.0 mos (6.4, 13.3); HR=0.81 (0.59, 1.10), p=0.18. Estimated 1-year survival was higher with AZA vs CCR in all cytogenetic risk subgroups. Twice the proportion of AZA-treated pts in the poor-risk subgroup were alive at 1 year vs. CCR pts (30.9% vs 14.0%, respectively), a clinically meaningful difference of 16.9% (95%CI 4.4, 29.5). Similarly, in the CN subgroup, 60.7% vs 44.1% of pts were alive at 1 year in the AZA and CCR groups, a difference of 16.5% (3.2, 29.8). AZA effect on 1-year survival in the INT-risk subgroup was also favorable (55.2% vs 45.5% with CCR) (difference 9.7% [-1.4, 20.8]). Grade 3-4 hematologic adverse event rates with AZA were consistent with previous reports (Santini, Eur J Haematol, 2010), with no meaningful differences among all cytogenetic risk groups. Conclusions: Median OS in older pts with AML and poor-risk cytogenetics was meaningfully improved with AZA compared with the CCR currently used for AML, with those pts receiving AZA twice as likely to be alive at 1 year as those treated with CCR. Figure 1 Figure 1. Figure 2 Figure 2. Disclosures Döhner: Celgene: Consultancy. Off Label Use: Use of azacitidine in AML with blast count >30%. Seymour:Celgene: Consultancy, Honoraria, Speakers Bureau. Wierzbowska:Celgene: Honoraria, Speakers Bureau. Selleslag:Celgene: Consultancy, Research Funding, Speakers Bureau. Cavenagh:Celgene: Honoraria. Kumar:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Schuh:Celgene: Membership on an entity's Board of Directors or advisory committees. Candoni:Celgene: Consultancy, Speakers Bureau. Récher:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding. Sandhu:Celgene: Honoraria. Bernal del Castillo:Celgene: Consultancy. Al-Ali:Celgene: Honoraria, Research Funding. Martinelli:Novartis: Consultancy, Speakers Bureau; BMS: Consultancy, Speakers Bureau; Pfizer: Consultancy; ARIAD: Consultancy. Falantes:Celgene: Consultancy. Stone:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees. Minden:Celgene: Honoraria. McIntyre:Celgene: Employment. Songer:Celgene: Employment, Equity Ownership. Lucy:Celgene: Employment, Equity Ownership. Beach:Celgene: Employment, Equity Ownership. Dombret:Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,006

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,007
Tête enseignante GPT0,227
Écart entre enseignants0,221 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations9
Publié2014
Routes d'admission1
Résumé présentoui

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